1. Field of Invention
This invention relates to a self generating power line ampacity system by object oriented modeling and expert rules of the power line environment.
2. Description of Related Art
Line ampacity system
Electric power companies generally determine the current carrying capacity of overhead power lines based upon conservative assumptions of ambient temperature, wind speed and solar radiation for a maximum allowable conductor temperature. Most common assumptions are: ambient temperature=40.degree. C., wind speed=1 m/s, solar radiation=1000 W/m.sup.2, maximum conductor temperature=80.degree. C. During favorable weather conditions when ambient temperature is lower than the assumed maximum or when wind speed is higher than the assumed minimum or during cloudy sky conditions higher ampacity is possible without exceeding the allowed maximum temperature of the power line conductor.
For the above reasons many utilities have started adapting line ratings to actual weather conditions as an inexpensive way to increase line capacity. Dynamic line rating systems are also proposed that take into account the heat storage capacity of the conductors. Ampacity systems that adjust line capacity depending upon measured conductor temperature or actual weather conditions require continuous input of data by the installation of line temperature sensors, meteorological sensors and/or on-line connection to a weather bureau. Sometimes elaborate telecommunication systems are also required to bring data from remote sensor locations to a host computer where line ampacity is evaluated. Real time line ampacity systems are therefore expensive to install, cumbersome to operate and maintain. The self generating line ampacity system hereafter called LINEAMPS provides an alternative method of obtaining line ampacity which does not require real time conductor temperature measurements or continuous input of meteorological data. It is a self generating line ampacity system because power line ampacity is estimated by weather station objects in the program that have data and methods to generate hourly values of ambient temperature, wind speed, wind direction and solar radiation. The system is therefore realized more economically and can be easily implemented in any region.
Another subject of recent interest is the development of forecasting models to determine power line ampacity several hours ahead into the future. Power system planners have load forecasting tools and also require advance knowledge of transmission and distribution line capacity. LINEAMPS is a tool that can be used by power system operators or anyone who is interested to know present and future power line capacity for the efficient operation of electric power system.
Electric power companies are also interested in new ways of operating power lines to maximize capacity utilization so that they may defer capital investment required for the construction of new lines. Delaying the construction of new lines is also beneficial to the environment. With the advent of newer technology, delaying the construction of new lines may eventually lead to their cancellation thereby saving large investments. LINEAMPS is a software tool enabling increased utilization of existing lines which can delay the construction of new lines and therefore has the potential to save large investments.
Estimation of power line ampacity by the application of object oriented modeling and expert rules was first presented by Deb in the following IEEE reference:
"Object oriented expert system estimates power line ampacity", by Anjan K. Deb, IEEE Computer Application in Power, volume 8, number 3, 1995.
Deb's line ampacity system has power line object, weather station object and conductor object. Power line objects contain data and methods which eliminates the need to read line data from external data files. Line ampacity results are also stored in the power line object data base slots. Thus the power line object not only offer methods required to calculate ampacity, it is also a convenient repository for the storage of line data and its ampacity that can be easily retrieved and presented on the screen. Deb's object oriented power line ampacity system also provides greater user facility to input data, management of power line, weather and conductor data, and for the presentation of results.
Previously Deb developed time series stochastic and deterministic models that are given in the following references:
"Le systeme ATLAS de PG&E d'evaluation dynamique de la capacite thermique d'une ligne de transport," by L. Cibulka, W. J. Steeley, A. K. Deb, Conference Internationale des Grands Reseaux Electriques, Paris, France, Aug. 30 to Sep. 5, 1992.
"Ambient temperature corrected dynamic transmission line ratings at two PG&E locations", by W. J. Steeley, B. L. Norris, A. K. Deb, IEEE Transactions on Power Delivery, Volume 6, Number 3, July 1991, pages 1234-1242.
"Dynamic thermal rating of transmission lines independent of critical span analysis," by T. Paul Mauldin, William J. Steeley, A. K. Deb, International Conference on High Technology in the Power Industry, Phoenix, Ariz., USA, Mar. 1-4, 1988.
In the above references line ampacity was based on ambient temperature measurements only by assuming constant wind speed.
In the following reference:
"Prediction of overhead transmission line ampacity by stochastic and deterministic models," by J. F. Hall and A. K. Deb, published in the IEEE Transactions on Power Delivery, Vol. 3, No. 2, April 1988, pages 789-800,
Deb presented a stochastic model to forecast wind speed also. A limitation of these models are that they require hourly measurement of meteorological data on a continuous basis to calculate stochastic variables Z(t-1), Z(t-2) shown below, EQU Ta(t)=A.sub.1 +A.sub.2 .multidot.Sin (2.omega.t)+A.sub.3 .multidot.Sin (2.omega.t)+A.sub.4 .multidot.Cos (.omega.t)+A.sub.5 .multidot.Cos (2.omega.t)+A.sub.6 .multidot.Z(t-1)+A.sub.7 .multidot.Z(t-2)
where,
Z(t-1), Z(t-2)=difference in measured and predicted temperature at time (t-1) and (t-2) respectively.
A.sub.1, A.sub.2, A.sub.3, A.sub.4, A.sub.5, A.sub.6, A.sub.7 are the coefficients of the model .omega.=2p/T=fundamental frequency
T=24 hour=period
In my LINEAMPS stochastic variables are not required and extended Fourier series models of ambient temperature and wind speed are used to generate weather data which eliminates the need for real time measurements. Another limitation of the stochastic model is that it is unsuitable for the predictions of hourly values of ambient temperature for more than twenty-four hours in advance. This is to be expected, as the time series statistical model does not consider a physical model of the atmosphere, as the national weather service does for long-term weather predictions.
A weather dependent line rating method was proposed in the following reference:
"Weather-dependent versus static thermal line ratings," by Dale A. Douglass, IEEE Power Engineering Society, Transmission and Distribution Meeting, Anaheim, Calif., Sep. 14-19, 1986, paper 86 T&D 503-7.
Douglas's method also required hourly input of weather data from a weather bureau on a continuous basis. Moreover, the proposed method did not recognize the diurnal weather patterns of the region for the prediction of line ampacity. The existence of daily and seasonal cyclical weather patterns are well known and their usefulness to forecast power line ampacity has been recognized in the following references:
"Prediction of overhead transmission line ampacity by stochastic and deterministic models," by J. F. Hall, A. K. Deb. IEEE Transactions on Power Delivery, Vol. 3, No. 2, April 1988, pages 789-800.
"Higher service current in overhead lines," by A. K. Deb, S. N. Singh, T. K. Ghoshal, CIGRE Brussels Symposium on High Currents in Electric Network under Normal and Emergency Conditions, June 1985, Brussels, Belgium.
"Dynamic line rating in the operating environment," by Stephen D. Foss, Robert A. Maraio (IEEE Transmission and Distribution Conference paper # 89 TD 431-8 PWRD 1989).
In LINEAMPS the periodic cyclical pattern of wind speed and ambient temperature are considered in a unique manner to forecast power line ampacity. Weather patterns of a region are stored by Fourier series in each weather station object. A method in each of the weather station objects generates hourly values of meteorological data from this series. The power line object have plurality of virtual weather sites that receive their data from plurality of weather station objects and a method in each power line object determines the minimum hourly values of line ampacity up to seven days in advance. The number of virtual weather stations that can be accommodated in a power line is limited only by the computer processing speed and memory whereas installing unlimited number of line temperature sensors is not economical. Due to these reasons LINEAMPS is unique and expected to be more reliable and more accurate than systems utilizing real time measurements from limited number of locations.
Dynamic line rating system
A real time dynamic line rating model was proposed in the following reference:
"Real-time ampacity model for overhead lines," by W. Z. Black, W. R. Byrd, IEEE transactions on power apparatus and systems, Vol. PAS-102, No. 7, July 1983.
In Black and Byrd's method, line ampacity is predicted accurately by real time numerical solution of conductor temperature differential equation at a location. The system requires real time conductor temperature and meteorological data on a continuous basis and does not have weather models to forecast line ampacity up to seven days in advance. LINEAMPS is an integrated line ampacity having weather models to forecast line ampacity up to seven days in advance. LINEAMPS has provision for steady state ratings, dynamic line ratings, and transient ratings that are based upon user input and a direct solutions of the conductor temperature differential equation is used to obtain dynamic line ratings.
U.S. Pat. No. 5,140,257
U.S. Pat. No. 5,140,257 was issued to M. Davis for a transmission line rating system that calculates the current carrying capacity of one or more power lines by the measurement of conductor temperature and meteorological conditions on the line. Line ampacity is calculated by the solution of conductor heat balance equation. Davis's system requires the installation of conductor temperature sensors as well as meteorological sensors at several locations along power lines. Real time conductor temperature, meteorological data and line current are continuous input to a computer system where line ampacity is calculated. The computer system requires specialized hardware and software for data acquisition from remote sensor locations via special telecommunication networks. Because of these requirements the system could not be applied or commercialized in a wide scale. LINEAMPS does not require real time continuous input of meteorological data, line current or conductor temperature measurements from the power line. Power line and conductor ampacity is estimated by LINEAMPS from user input and by synthetic generation of weather data from self generating weather stations objects in the program.
Synthetic generation of weather data
An important contribution of this invention is the ability to self generate hourly values of weather data from statistical and analytical models eliminating the need for real time continuous input of data. Deb has previously developed algorithms for synthetic generation of weather data by time series analysis in the above mentioned references. The idea of self generation, synthetic generation, or artificial generation of meteorological data by Fourier series of ambient temperature and wind speed of a region has evolved from these developments.